TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Designing Reactive AI With Spiking Neural Nets

Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.
IEEE

Graph Neural Network-based GrUNet and Attention Transformer Adjacency Matrix for Video Denoising

Abstract: Videos account for a significant portion of internet traffic, and the presence of noise, whether from compression algorithms, low light, sensor imperfections, deteriorates the video quality.
eeworldonline

AI-native chip with integrates 2 MB SRAM, Cortex-M4F CPU and analog sensor interfaces

Ambient Scientific has introduced the GPX10 Pro, a system-on-chip designed specifically for edge AI applications. The device implements ten programmable AI cores based on the company’s DigAn silicon ...
SiliconANGLE

D-Matrix introduces AI network accelerator card for ultra-low-latency inference

Artificial intelligence computing infrastructure startup d-Matrix Corp. today unveiled a custom network card named JetStream designed from the ground up to support high-speed, ultra-low-latency AI ...
IEEE

Hierarchical Matrices in Graph Convolutional Deep Neural Network Context: Performance Evaluation in a Case Study

Abstract: This paper explores the integration of Hierarchical Matrices (H-matrices) within Graph Convolutional Deep Neural Networks (GC-DNNs) laying the foundations to assess their performance in a ...
EurekAlert!

Cutting-edge algorithms promise to speed up therapeutic discovery in healthcare

Imagine giving a familiar medication a whole new purpose—finding fresh treatments without starting from scratch. That’s precisely what a team of researchers at Xidian University in China has been ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...
Frontiers

Explainable graph neural network based on metabolic brain imaging for differential diagnosis of parkinsonism

Background: Accurate differentiation of parkinsonian syndromes remains challenging due to overlapping clinical manifestations and subtle neuroimaging variations. This study introduces an explainable ...
Scientific Research Publishing

Liu, Y., Pu, H. and Sun, D. (2021) Efficient Extraction of Deep Image Features Using Convolutional Neural Network (CNN) for Applications in Detecting and Analysing Complex Food ...

ABSTRACT: The food recognition systems are available for foreign dishes but much work has not been done for our traditional dishes making it difficult to classify the traditional dishes and the ...